Electrical devices identification model for the identification of electrical devices by analyzing their energy consumption profiles
| dc.contributor.advisor | Kurnaz, Sefer | |
| dc.contributor.author | Al-Obaidi, Maan Hani Nassar | |
| dc.date.accessioned | 2023-02-09T13:36:51Z | |
| dc.date.available | 2023-02-09T13:36:51Z | |
| dc.date.issued | 2022 | en_US |
| dc.date.submitted | 2022 | |
| dc.department | Enstitüler, Lisansüstü Eğitim Enstitüsü, Elektrik ve Bilgisayar Mühendisliği Ana Bilim Dalı | en_US |
| dc.description.abstract | Monitoring frameworks utilizing picture handling has acquired substantially more consideration among the specialists on the moving characteristics like low-costs, dependability and adaptability towards consolidating with different innovations. Accordingly, the timberland fire location framework is planned by creating discovery calculations utilizing pictures and the picture handling procedures, to distinguish the occasions of fire dependent on the affirmation from the Monitoring Centers. In this investigation work, the attestation of a fire alert is helped through the proposed fire really take a look at estimation. The fire check estimation is proposed for the request for fire picture and non-fire pictures for the decline of counterfeit alerts using picture taking care of moves close. For the extraction of data from an info picture, a histogram evening out, RGB disguising space, and YCbCr model based framework is imagined. The organizing of fire and non-fire symbolism is portrayed through rule-based portrayal. The power makeover of fire concealing pixels in the data image is given by histogram change, which is likewise dealt with for the extraction of RGB parts. The RGB parts that have been erased are given to the change stage, where the picture is changed over to a YCbCr disguising model for segregating luminance from chrominance. | en_US |
| dc.identifier.citation | Al-Obaidi, Maan Hani Nassar. (2022). Electrical devices identification model for the identification of electrical devices by analyzing their energy consumption profiles. (Yayınlanmamış yüksek lisans tezi). Altınbaş Üniversitesi, Lisansüstü Eğitim Enstitüsü, İstanbul. | en_US |
| dc.identifier.uri | https://hdl.handle.net/20.500.12939/3277 | |
| dc.identifier.yoktezid | 768349 | |
| dc.institutionauthor | Al-Obaidi, Maan Hani Nassar | |
| dc.language.iso | en | |
| dc.publisher | Altınbaş Üniversitesi / Lisansüstü Eğitim Enstitüsü | en_US |
| dc.relation.publicationcategory | Tez | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Forest Fires | en_US |
| dc.subject | Image Processing Algorithm | en_US |
| dc.subject | Fire Detection | en_US |
| dc.subject | Classification Algorithm | en_US |
| dc.title | Electrical devices identification model for the identification of electrical devices by analyzing their energy consumption profiles | |
| dc.type | Master Thesis |
